Photo/iStock.
USC researchers will present 19 papers at the 34th Conference on Neural Information Processing Systems (NeurIPS 2020), a virtual-only event running Dec. 5 through 12.
Launched in 1986, the annual machine learning and computational neuroscience conference has evolved into one of the world’s leading AI gatherings. With 38% more paper submissions than 2019, this has been another record-breaking year for NeurIPS. A total of 1,903 papers were accepted, compared to 1,428 last year. The NeurIPS 2020 paper acceptance rate is 20.1 percent — slightly lower than last year’s 21 percent.
USC Papers:
How does This Interaction Affect Me? Interpretable Attribution for Feature Interactions
Michael Tsang (USC)*; Sirisha Rambhatla (USC); Yan Liu (USC)
Theoretical Insights into Multiclass Classification: A High-dimensional Asymptotic View
Christos Thrampoulidis (University of California, Santa Barbara)*; Samet Oymak (University of California, Riverside); Mahdi Soltanolkotabi (USC)
Bias No More: High-Probability Data-Dependent Regret Bounds for Adversarial Bandits and MDPs
Chung-Wei Lee (USC); Haipeng Luo (USC)*; Chen-Yu Wei (USC); Mengxiao Zhang (USC)
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition
Tiancheng Jin (USC)*; Haipeng Luo (USC)
A Scalable Approach for Privacy-Preserving Collaborative Machine Learning
Jinhyun So (USC)*; Basak Guler (USC); Salman Avestimehr (USC)
Classification with Valid and Adaptive Coverage
Yaniv Romano (Stanford University)*; Matteo Sesia (USC); Emmanuel Candes (Stanford University)
Songtao Lu (IBM Research)*; Meisam Razaviyayn (USC); Bo Yang (University of Minnesota); Kejun Huang (University of Florida); Mingyi Hong (University of Minnesota)
A General Large Neighborhood Search Framework for Solving Integer Linear Programs
Jialin Song (Caltech)*; Ravi Lanka (Jet Propulsion Laboratory); Yisong Yue (Caltech); Bistra Dilkina (USC)
Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition
Lin Chen (University of California, Berkeley)*; Qian Yu (USC); Hannah Lawrence (Flatiron Institute); Amin Karbasi (Yale)
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
Chaoyang He (USC)*; Murali Annavaram (USC); Salman Avestimehr (USC)
Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels
Yi Zhou (USC)*; Chenglei Wu (Facebook Reality Labs); Zimo Li (USC); Chen Cao (Facebook Reality Labs); Yuting Ye (Facebook Reality Labs); Jason Saragih (Facebook); Hao Li (Pinscreen/USC/USC ICT); Yaser Sheikh (Facebook Reality Labs)
Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes
Dongsheng Ding (USC)*; Kaiqing Zhang (University of Illinois at Urbana-Champaign (UIUC)); Tamer Basar (University of Illinois at Urbana-Champaign); Mihailo Jovanovic (USC)
Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss
Shuang Qiu (University of Michigan)*; Xiaohan Wei (USC); Zhuoran Yang (Princeton); Jieping Ye (Didi Chuxing & University of Michigan); Zhaoran Wang (Northwestern U)
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors
Karl Pertsch (USC)*; Oleh Rybkin (University of Pennsylvania); Frederik Ebert (UC Berkeley); Shenghao Zhou (University of Pennsylvania); Dinesh Jayaraman (University of Pennsylvania); Chelsea Finn (Stanford); Sergey Levine (UC Berkeley)
Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective
Vu Nguyen (Amazon Research Australia)*; Vaden Masrani (University of British Columbia); Rob Brekelmans (USC Information Sciences Institute); Michael A. Osborne (University of Oxford); Frank Wood (University of British Columbia)
Comparator-Adaptive Convex Bandits
Dirk van der Hoeven (Leiden University)*; Ashok Cutkosky (Google Research); Haipeng Luo (USC)
Multi-agent Trajectory Prediction with Fuzzy Query Attention
Nitin Kamra (USC)*; Hao Zhu (Peking University); Dweep Kumarbhai Trivedi (USC); Ming Zhang (Peking University); Yan Liu (USC)
Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks
Seyed Mohammadreza Mousavi Kalan (USC)*; Zalan Fabian (USC); Salman Avestimehr (USC); Mahdi Soltanolkotabi (USC)
Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning
Sirisha Rambhatla (USC)*; Xingguo Li (Princeton University); Jarvis Haupt (University of Minnesota)
Published on December 4th, 2020
Last updated on February 23rd, 2021
